The present invention relates to a method for evaluating operability of an object recognition device of a motor vehicle by using a camera simulation device. The invention also relates to a device for checking suitability of the camera simulation device for use in the evaluation of the operability of the object recognition device.
The following discussion of related art is provided to assist the reader in understanding the advantages of the invention, and is not to be construed as an admission that this related art is prior art to this invention.
An object recognition device can be used to identify and classify individual objects in an image or an image sequence based on automatic image processing. Such object recognition device can be used in a motor vehicle to automatically recognize other road users and obstacles in the surroundings of the vehicle and to provide on this basis a driver of the vehicle with support for steering the vehicle. For example, a lane departure assistant may be considered, initiating an emergency stop, recognition of traffic signs, recognition of pedestrians, or distance control. The images for the identification then originate from, for example, a video camera, an infrared camera or a 3-D camera, which may be located, for example, in the mirror base, in the side view mirror or in the trunk lid of the vehicle.
Before a certain model of an object recognition device can be used in a vehicle, extensive tests must be performed to determine if this experimental device satisfies the technical requirements. In other words, it must be determined if the model to be investigated is operational so as to be suited for use in a vehicle. Otherwise, for example, an emergency stop may be initiated due to an erroneous identification for no other reason which may potentially cause an accident. For evaluating the operability, i.e. for evaluating the object recognition device, the device must be tested for as many different environments and driving situations as possible.
For this purpose, film recordings may be used which were recorded during a test drive with the same camera model that is to be used later as an image source for the object recognition device itself. However, such test drives are relatively expensive.
In order to be able to evaluate the object recognition device for still more different routes at reasonable costs, the image data for testing the object identification device may not be generated with a camera, but based on a simulation. A simulator hereby computes, on one hand, the image information that would result from a camera angle of a camera built into the vehicle during the drive. On the other hand, the simulator also reproduces optical distortions and other effects misrepresenting the image information, which are produced by the camera when the camera captures the represented image and transmits the captured image data to the object recognition device. A simulator for such combined simulation of a route and an imaging characteristic of a camera is herein referred to as camera simulation device.
Because of the image data of a camera simulation device are generated artificially, an object recognition device developed based on the camera simulation device must operate error-free even with a real camera in a real driving situation. In other words, the simulation image data generated by the camera simulation device must have the most realistic appearance at least with reference to those features relevant for the object recognition. Such features may be, for example, the detailed reproduction of the simulated objects themselves, an imaging characteristic of a camera lens or noise of the image sensor of the camera.
Objects can be recognized, on one hand, based on of film recordings of real driving scenarios and, on the other hand, based on image sequences from a simulator. Should the results of the recognition for these two recognition attempts be different, then the simulation could not have been very realistic. In this case, the simulator is reconfigured.
However, the simulator must here disadvantageously be adapted to a specific type of object recognition device, namely the object recognition device used for configuring the simulator. Moreover, the simulator may then not always generate realistic simulation image data with respect to those features that are important for the recognition ability of another type of object recognition device. For this reason, when object recognition devices are developed, the simulator needs always to be reconfigured before new recognition algorithms are tested.
It would therefore be desirable and advantageous to obviate prior art shortcomings and to provide an improved and more cost-effective object recognition device for a motor vehicle.